Solving some large-scale problems entails analyzing the manner in which a very large number of nodes are linked in a very large network (e.g., a network of millions or billions of nodes interconnected with millions or billions of links). The nodes of such networks may represent people or any of a variety of types of objects, and the links may represent any of a variety of relationships (e.g., connections in a social network) or interactions (e.g., exchanges of voice or data communications) between those nodes. Real-world networks often have a structure in which there are clusters or “communities” of densely interconnected nodes separated by portions of the network where the nodes are less densely interconnected. Identifying such communities is often a part of analyzing very large networks, and often requires significant processing resources and time.